Understanding Biostatistics looks at the fundamentals of biostatistics, using elementary statistics and explores the nature of statistical tests. This book is intended to complement first-year statistics and biostatistics textbooks. The main focus here is on ideas, rather than on methodological details. Basic concepts are illustrated with represenations from history, followed by technical discussions on what different statistical methods really mean. graphics are used extensively throughout the book in order to introduce mathematical formulae in an accessible way. Key features: • Discusses confidence intervals and p-values in terms of confidence functions. • Explains basic statistical methodology represented in terms of graphics rather than mathematical formulae, whilst highlighting the mathematical basis of biostatistics. • Looks at problems of estimating parameters in statistical models and looks at the similarities between different models. • Provides an extensive discussion on the position of statistics within the medical scientific process. • Discusses distribution functions, including the Gaussian distribution and its importance in biostatistics. This book will be useful for biostatisticians with little mathematical background as well as those who want to understand the connections in biostatistics and mathematical issues. Contents 1 Statistics and Medical Science. 2 Observational Studies and the Need for Clinical Trials. 3 Study Design and the Bias Issue. 4 The Anatomy of Statistical Tests. 5 Learning About Parameters, and Some Notes on Planning. 6 Empirical Distribution Functions. 7 Correlation and Regression in Bivariate Distributions 8 How to Compare the Outcome in Two Groups. 9 Least Squares, Linear Models and Beyond. 10 Analysis of Dose response. 11 Hazards and Censored Data. 12 From the Log-rank Test to the Cox Proportional Hazards Model. 13 Remarks on Some Estimation Methods. Index.

About the Book Majority of medical investigations depend on probability and sample study. These two topics have been discussed and explained at great length with reference to anatomy where possible. The concepts have been explained in a way useful for practical applications. Very clear and conceptual mathematical treatment has been given for Kaplan--Meier model. The book is suitable for students at the undergraduate/postgraduate level. Researchers and statisticians working in the field of medicine and other areas in life sciences will also find this book extremely useful. Contents 1. Introduction and Basic Concepts 2. Statistical Averages and Dispersion 3. Probability and Mathematical Expectation 4. Probability Distributions 5. Correlation 6. Regression Analysis 7. Sampling Theory and Testing of Hypothesis 8. Vital Statistics 9. Survival Analysis About the Authors B. M. Aggarwal, did B.Sc. Hons in Mathematics from Punjab University, and M.Sc Mathematics from Merrut University. Later he graduated in B.Tech (FIETE) from the Institute of Electronics and Telecommunication Engineers, New Delhi. In addition, he passed certificate courses in Microwave and Satellite Engineering from ALT Centre, Ghaziabad. The author is a visiting professor in Statistics, Quantitative techniques, operations research and research methods at various premier institutes like IMT Ghaziabad, ICFAI Gurgaon, Asia Pacific Institutes of Management ,New Delhi Institute of Management, Delhi besides several other Institutes. He has about ten books to his credit. Dr. Pulin Kumar Gupta, M.D (Medicine) FIACM is currently Professor at the Department of Medicine, PGIMER, Dr. RML Hospital, New Delhi.